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Thesis - University Access Only
Master of Science (MS)
Electrical Engineering and Computer Science
Recent advances in the deep space exploration have posted considerable challenges on communication systems. The high volume of multimedia data generated by various exploration missions is becoming dominating over the InterPlaNetary (IPN) Internet. Therefore, the challenges posed by the multimedia communication Quality of Service (QoS) over IPN networks with energy-constraints need to be addressed. Reliable and energy-efficient multimedia transmission in such deep-space IPN faces critical challenges including energy efficiency and service quality guarantee. In this thesis, a framework is proposed to optimally allocate the transmission power resources in the IPN networks, in order to achieve the maximized QoS. The transmission power among intra-inter frames and divers relay stations are adaptively adjusted and joint considered with the communication service performance and energy consumption budget. The main contribution of this paper includes three folds. First, an Unequal Error Protection (UEP) adaptive power control scheme is proposed to achieve system level QoS maximization under strict energy budgets. Second, based on the full exploration of intra-inter frame and relay diversity two global algorithms – genetic based and global search – are proposed to improve video quality by best allocating the limited energy. Third, the two proposed approach is suitable to support both real-time and non-real application in the future deepspace missions. Extensive simulation results in terms of the system QoS performance reveal the potential of the proposed adaptive power control strategy in the IPNs as a future supporting network architecture solution.
Library of Congress Subject Headings
Data transmission systems
Includes bibliographical references (pages 51-57)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Wang, Chunqiu, "Optimal Transmission Power Selection for Deep Space Communication Services Under Energy Constraints" (2014). Electronic Theses and Dissertations. 2041.